Promoting equal access to consumer credit has long been a policy goal in the United States. But is credit shared equally between spouses? There are reasons to believe that disparities in credit persist within a marriage. Survey evidence shows that perceived financial inequity between spouses is among the top predictors of divorce in the U.S.1 For married couples with a single household income—roughly half of married couples with at least one child2—breadwinners likely have higher borrowing capacity than their spouses, because income determines at least part of one’s ability to borrow. However, the role of access to credit within a marriage has been understudied, and we know little about the extent and implications of credit disparities between spouses. 

This research brief summarizes results published by Kim (2021), which uses de-identified JPMorgan Chase financial accounts data to document gaps between spouses in credit access and consumption.3 The research evaluates the impact of the 2013 reversal of the Truth-in-Lending-Act (TILA) on these intra-household inequalities. Before November 2013, TILA Section 150—which imposes ability-to-pay requirements in the U.S. consumer credit card market—required credit card issuers to evaluate applicants’ independent (i.e., individual) income in their lending decisions. This independent income requirement raised concerns that credit access for secondary earners or stay-at-home spouses may be restricted because these spouses had access to household income but had limited income of their own. The statute was reversed in November 2013 to allow credit card issuers to consider household income, facilitating access to credit for secondary earners and stay-at-home spouses. How did spouses differ in their access to credit and consumption patterns prior to November 2013, and did the TILA reversal changes those patterns?

Inequalities between spouses in access to credit and consumption prior to the TILA reversal

  • There were large gaps in credit access between spouses (Figure 1): Before the TILA reversal, primary earners had access to 97% and secondary earners or stay-at-home spouses (henceforth, “secondary earners”) 29% of total available credit limits at the household-level, indicating the average credit gap between spouses was 68%.4 This implies prior to November 2013, secondary earners could borrow 30 cents for every dollar primary earners could borrow. The gap in independent credit access between spouses is even larger (72%), suggesting secondary earners were much less likely than primary earners to be able to borrow independently from credit markets prior to the TILA reversal.
  • There were large gaps in consumption within the household: Before the TILA reversal, primary earners consumed 59% and secondary earners 41% of total monthly household consumption, indicating the average consumption gap between spouses of 18%. This implies secondary earners consumed 69 cents for every dollar consumed by primary earners prior to the TILA reversal.

Figure 1: There were large gaps between spouses in access to credit and consumption prior to the TILA reversal.

Bar Chart

Bar chart showing the average monthly share of total accessible household credit, independently accessible household credit,  and household consumption by spouse prior to the TILA reversal (Oct. 2012 to Oct. 2013). The spouse groups are primary earner and secondary earner.  Prior to the reversal, prim,ary earners had higher access to credit and consumed more relative to secondary earners.

SOURCE:JPMORGAN CHASE INSTITUTE

What happened when secondary earners were allowed to apply for credit based on household income as a result of the 2013 TILA reversal?

  • Secondary earners’ credit access increased by more than $1,000 over the two-year period after the TILA reversal (Figure 2). This increase is economically meaningful, representing 40 percent relative to secondary earners’ baseline average monthly consumption, where the baseline period refers to one full year before the reversal, October 2012 to October 2013. The effects are larger for stay-at-home spouses, consistent with the TILA reversal having a larger effect on spouses who have limited income of their own.
  • The TILA reversal increased secondary earners’ consumption level and share of household consumption (Figure 2). Secondary earners’ consumption increased by 14 percent relative to their baseline average monthly consumption, or roughly $340. The share of consumption allocated to secondary earners increased by 5 percent relative to their pre-reversal average monthly consumption share, indicating that spouses shared consumption more equally.
  • The TILA reversal increased household credit commensurately, but resulted in only a small increase in household consumption (Figure 2). Total credit limits available at the household-level increased by 20 percent relative to pre-reversal average monthly household consumption, or $1,158. The size of the effect for household credit limit is about the same as that for secondary earners, implying the reversal did not crowd out primary earners’ credit, but expanded the secondary earners’ or stay-at-home spouses’ credit access. Household consumption increased by 3 percent relative to pre-reversal average monthly household consumption, or roughly $170.
  • The TILA reversal did not negatively impact the financial well-being of the household. Over the two-year period following the TILA reversal, a variety of financial solvency outcomes were not materially impacted, including credit card delinquency rates or overdraft probabilities.

Figure 2: The 2013 TILA reversal materially increased access to credit and consumption for secondary earners and particularly within single-income households.

Bar Chart

Bar chart showing the differential dollar change in credit limits and consumption for secondary earners and households in equitable distribution states relative to community property states after the 2013 TILA reversal by household type. The household groups are all households and single-income households. After the reversal, the credit limit and consumption of secondary earners in equitable distribution states increased relative to community property states. The reversal increased household credit commensurately, but resulted in only a small increase in household consumption. The estimated changes are more pronounced for single-income households.

SOURCE: JPMORGAN CHASE INSTITUTE

Policy Implications: Lessons learned from the 2013 TILA reversal 

  • Underwriting standards and financial policies can have an uneven impact on individual family members in the household.
  • Policies aimed at reducing financial disparities between spouses—such as underwriting standards based on household rather than individual marital assets and income can improve the financial imbalance between spouses and reduce consumption inequality.
  • Efforts to expand access to credit—in this case to secondary earners and stay-at-home spouses within the household—can achieve welfare gains for historically underserved members of the community without necessarily resulting in worse credit outcomes or financial distress for the household. The TILA reversal did just that. 

Appendix

Data Appendix

Sample

We use de-identified administrative data on Chase deposit account, debit card, and credit card customers to construct a sample of 66,200 opposite-sex couples from October 2012 and December 2015, covering one year before and two years after the TILA reversal. At the end of data construction steps, we have a monthly household panel dataset that tracks spending and credit card outcomes for each spouse.

To construct the sample of 66,200 households (henceforth “All Sample”), we make two types of sample restrictions: demographic and account activity. We apply the following demographic filters. We focus on individuals in working age (25 to 65 years old) as of November 2013, or when the TILA reversal was implemented. We consider two opposite-sex adults with less than 16 years of age gap and the same last name residing in the same address as a household/family unit.5 Because individuals’ marital status is not directly observed, the gender composition and age gap restrictions are applied to focus on the sample that is most likely to represent married couples. Thus, the two adults in a household unit are assumed to be a married couple. Note that this sample restriction leaves many other types of household units, such as domestic partnership, same-sex couples, cohabiting couples, married couples with different last names, or married couples that live apart, among others.

Using this sample of two adult-member households, we apply the following account activity filters. We focus on spouses who are either a primary or secondary account holder of at least one active (i.e., having at least 5 transactions every month) Chase personal checking account. Since we do not require each spouse to have a separate checking account, this sample captures a wide range of account structure types, such as couples with only one joint checking account as well as those with both joint and separate accounts. For couples with joint accounts, we require spouses to have their own debit card associated with these shared accounts to be able to track each spouse’s spending on the joint accounts. We further restrict the sample to couples that make above poverty threshold annual labor income in 2013.6 We require at least one spouse to have a Chase personal credit card. Finally, we focus on couples where secondary earners did not have a sole Chase personal credit card account as of the beginning of the sample period (October 2012). This restriction allows us to focus on a sample of new credit card openers who are required to report income on their credit card applications around the TILA reversal.

We create a subsample of roughly 11,700 households (henceforth “Card Holder Sample”) where secondary earners eventually opened a sole personal Chase credit card at some point during the sample period. This helps to focus on the subsample of households where the credit gap between spouses eventually changed following the TILA reversal. For detailed rationale behind sample construction criteria and variable construction method, see Kim (2021) Section 4.

Measurement

  • Consumption: monthly spouse-specific consumption is proxied by spending on each spouse’s financial accounts. Specifically, spouse’s consumption is defined as the sum of all spending categories on ’s sole and joint credit card, debit card, and checking accounts, including cash withdrawals and electronic transfers. To identify who spent what on the couples’ joint checking accounts, we identify which debit card is linked to whom and attribute spending to the respective debit card holder. For all other joint account transactions where the identity of the spender cannot be identified (e.g., joint credit card accounts where individual card holder cannot be identified or non-debit joint checking account transactions, such as electronic transfers), we assume that spouses equally shared these expenses.7 We define household consumption as the sum of the two spouses’ individual consumption and spouse-specific consumption shares as each spouse’s spending relative to total household spending.
  • Credit: We construct two credit measures—independent credit and total credit. Spouse’s independent credit access is proxied by the sum of credit limits on each spouse’s sole credit card account; and ’s total credit access is the sum of credit limits on any credit card account he or she has access to either as a primary account holder or as an authorized user. Household credit access is measured as the sum of credit limits available to spouses and captures the couples’ total borrowing capacity if they pooled credit together. Credit limits on joint accounts are only counted once in the household-level aggregation.
  • Income: monthly spouse-specific income is measured as the sum of labor income (payroll direct deposits), government transfers, and other income deposited to spouses’ sole and joint checking accounts for which they are the primary account holder. Since it is difficult to identify who earned what on the couples’ joint checking accounts, we treat the primary account holder as the earner of any income deposited to joint accounts. Using this income measure, we assume that a spouse is primary earner if he or she earned higher average monthly labor income relative to the other spouse in the pre-reversal period. A household is dual-income if (i) it receives more than 4 payroll direct deposits in a month; or (ii) receives more than 2 payroll deposits in a month and the difference in the amount deposited in each paycheck is larger than one standard deviation of monthly labor income that household receives on average.8 Households that are not classified dual-income are classified as single-income, and the lower- or non-earning partner in single-income households is assumed to be a stay-at-home spouse. There are two limitations of this income measure. First, each spouse’s level of income is likely to be inaccurate for dual-earner households where spouses deposit their respective income into joint accounts. Second, we may misclassify which spouse is the primary earner since we cannot cleanly identify which income streams belong to whom if both spouses deposit income into their joint checking accounts. For detailed discussions on why this mismeasurement is unlikely to bias estimated results, see Kim (2021) Section 4.2.

References

1.

See Dew, Britt, and Huston (2012) for survey evidence.

2.

Source: U.S. Bureau of Labor Statistics. This statistic refers to the share of non-dual income households amongst consumer units that reported having a spouse and at least one child under age 18.

3.

This study considers two opposite-sex adults with less than 16 years of age gap and the same last name and address as a household/family unit. The two adults in a household unit are assumed to be a married couple.  This sample restriction leaves many other types of household units, such as same-sex couples, cohabiting couples, married couples with different last names, or married couples that live apart.

4.

See the measurement section in data appendix for how stay-at-home spouses are defined.

5.

Note that researchers do not directly observe individuals’ address and family names as they are de-identified. 

6.

$17,000 is the U.S. Department of Health and Services’ 2013 poverty threshold for two-member household. 

7.

For example, if a joint checking account shows an electronic bill payment of $100, we attribute $50 to one spouse and $50 to the other spouse.

8.

Given that wage earners typically receive income on a bi-weekly basis (U.S. Bureau of Labor Statistics, 2020), the frequency of payroll deposits and the payroll difference between spouses helps to identify double income households.

Acknowledgements

We thank our research team for their hard work and contribution to this research, in particular, Damon Swaner in Consumer Banking & Fraud for sharing his insights on the TILA reversal and how it was implemented in practice. Additionally, we thank Emily Rapp, Annabel Jouard and Kristine Pham for their support. We are indebted to our internal partners and colleagues, who support delivery of our agenda in a myriad of ways, and acknowledge their contributions to each and all releases.

We are also grateful for the invaluable constructive feedback we received from external experts and partners. We are deeply grateful for their generosity of time, insight, and support.

We would like to acknowledge Jamie Dimon, CEO of JPMorgan Chase & Co., for his vision and leadership in establishing the Institute and enabling the ongoing research agenda. We remain deeply grateful to Peter Scher, Vice Chairman, Demetrios Marantis, Head of Corporate Responsibility, Heather Higginbottom, Head of Research & Policy, and others across the firm for the resources and support to pioneer a new approach to contribute to global economic analysis and insight.

Disclaimer

This material is a product of JPMorgan Chase Institute and is provided to you solely for general information purposes. Unless otherwise specifically stated, any views or opinions expressed herein are solely those of the authors listed and may differ from the views and opinions expressed by J.P. Morgan Securities LLC (JPMS) Research Department or other departments or divisions of JPMorgan Chase & Co. or its affiliates. This material is not a product of the Research Department of JPMS. Information has been obtained from sources believed to be reliable, but JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively J.P. Morgan) do not warrant its completeness or accuracy. Opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. No representation or warranty should be made with regard to any computations, graphs, tables, diagrams or commentary in this material, which is provided for illustration/reference purposes only. The data relied on for this report are based on past transactions and may not be indicative of future results. J.P. Morgan assumes no duty to update any information in this material in the event that such information changes. The opinion herein should not be construed as an individual recommendation for any particular client and is not intended as advice or recommendations of particular securities, financial instruments, or strategies for a particular client. This material does not constitute a solicitation or offer in any jurisdiction where such a solicitation is unlawful.

Suggested Citation

Greig, Fiona, Olivia Kim. 2022. “Credit and the Family: The Economic Consequences of Closing the Credit Gap of US Couples” JPMorgan Chase Institute. https://www.jpmorganchase.com/insights/all-topics/financial-health-wealth-creation/credit-and-the-family-truth-in-lending-act

Authors

Fiona Greig

Former Co-President

Olivia Kim